The uncertainty studied in this paper concerns the weather. The authors note that "in India the India Meteorological Department (IMD) has been issuing annual forecasts of the monsoon across the subcontinent since 1895, and it is widely reported in the Indian media that farmers’ livelihoods depend upon the accuracy of the forecast." From the introduction [emphasis added]:
"It is well‐established that agricultural profits in developing countries depend strongly on
weather realizations. It is similarly well‐known from the development economics literature that farmers without access to good insurance markets act conservatively, investing less on their farms and choosing crop mixes and cultivation techniques that reduce the volatility of farm profits at the expense of lower expected profits. Economists have focused valuable attention on policies and programs that can provide improved ex post mechanisms for dealing with the consequences of this variability. For example, innovations in insurance can spread risk across broader populations, or improved credit or savings institutions can permit more effective consumption‐smoothing over time...
Economists, however, have paid little attention to directly improving farmers’ capacity to dealHere's a bit about the methodology and results:
with weather fluctuations by improving the accuracy of forecasts of inter‐annual variations in weather. Like actuarially fair insurance, a perfectly accurate forecast of this year’s weather pattern, provided before a farmer makes his or her production decisions for the season, eliminates weather risk. However, a perfect forecast permits the farmer to make optimal production choices conditional on the realized weather and thus achieve higher profits on average compared with a risk‐neutral or perfectly‐insured farmer. The profit and welfare gains associated with improvements in the accuracy of long‐range forecasts (forecasts that cover, for example, an entire growing season) are potentially enormous, given the tremendous variability in profits and optimal investment choices across weather realizations."
"In this paper we used newly‐available panel data on farmers in India to estimate how the
returns to planting‐stage investments vary by rainfall realizations using an IV strategy in which the Indian forecast of monsoon rainfall serves as the main instrument. We show that the Indian forecasts significantly affect farmer investment decisions and that these responses account for a substantial fraction of the inter‐annual variability in planting‐stage investments, that the skill of the forecasts vary across areas of India, and that farmers respond more strongly to the forecast where there is more forecast skill and not at all when there is no skill. Our profit‐function estimates indicate that Indian farmers on average under‐invest, by a factor of three, when we compare actual levels of investments with the optimal investment level that maximizes expected profits over the full distribution of rainfall realizations.
We also used our estimates to quantify how farmers’ responses to the forecast affect both theObviously, weather realizations affect farmers' livelihood. But the precision with which farmers can predict the weather ahead of time also affects their livelihood: less precision (more uncertainty) reduces investment and reduces expected profits. The above allusion to "a warmed climate" is an example of what an "uncertainty shock" could be in this context. If climate change increases weather volatility, then without an improvement in forecast skill, there would be more uncertainty. The model in the paper can get at quantifying the impact of that uncertainty shock. The paper also mentions a new government policy aimed at improving the economy through reducing uncertainty. Monsoon Mission, launched in India in 2012, has a five-year budget of $48 million to support research on improving weather forecasting ability.
level and variability in profits... These indicated that farmer’s use of the forecasts increased average profit levels but also increased profit variability compared with farmers without access to forecasts. Indeed, based on the actual behavior of the farmers, our estimates indicated that they do better than farmers who would undertake optimal, unconstrained investments but have no forecasts when rainfall realizations are high, but worse under adverse rainfall conditions. Finally, we also assessed how profit levels would increase in the future as forecast skill increases under current climate conditions and under conditions predicted by climate models. These exercises indicate that even modest skill improvements would substantially increase average profits, and slightly more so in a warmed climate."